Application of Image Morphology in Detecting and Extracting the Initial Welding Position

A method of image morphology in detecting and extracting the initial welding position during the autonomous welding process is described.During the process,firstly visual sensing technology is used to capture the straight seam image,and secondly the image edges are detected by morphological corrosion edge detection algorithm,with which can retain the critical information while filter other interferences effectively at the same time.Then morphological processing algorithm is used to conduct the direction of filter by selecting the multidirectional linear structuring elements and finally get the initial weld position point coordinates with the Hough transform.The algorithm is simple,rapid,self-adaptability with high accuracy for interferences except long lines so as to accomplish the entire process of detecting the initial welding position.It can meet the practical demands of automatic guidance for robotic welding.

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

It has remained a hard nut for years to segment sonar images of jacket installation environment,most of which are noisy images with inevitable blur after noise reduction.For the purpose of solutions to this problem,a fast segmen-tation algorithm is proposed on the basis of the gray value characteristics of sonar images.This algorithm is endowed with the advantage in no need of segmentation thresholds.To realize this goal,we follow the undermentioned steps:first,calcu-late the gray matrix of the fuzzy image background.After adjusting the gray value,the image is divided into three regions:background region,buffer region and target regions.Afterfiltering,we reset the pixels with gray value lower than 255 to binarize images and eliminate most artifacts.Finally,the remaining noise is removed by morphological processing.The simulation results of several sonar images show that the algorithm can segment the fuzzy sonar images quickly and effectively.Thus,the stable and feasible method is testified.

Blind Source Separation based on Time-Frequency Morphological Characteristics for Rigid Acoustic Scattering by Underwater Objects

Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time-frequency Blind Source Separation （BSS） can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time-frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner-Ville Distribution （WVD） observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. A simulation experimental has been used to analyze the feasibility of the new method, with changing the pulse width of the transmitted signal, the relative amplitude and the time delay parameter. And simulation results show that the new method can not only separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.

Evaluation of Three-dimensional Urban Expansion: A Case Study of Yangzhou City, Jiangsu Province, China

With rapid urban development in China in the last two decades, the three-dimensional(3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area(two-dimensional(2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System(GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes.

3.0-Tesla:OPPORTUNITIES AND CHALLENGES

With the development of magnetic resonance （MR） technology, the concern is focused on molecular and physiological imaging besides structural information. Ultra high field MR scanner shows great superiority. 3.0-T MR scanners provide almost two-fold signal-to-noise ratio （SNR） compared with a standard 1.5-T MR scanner. The higher baseline SNR can be converted into a variety of alternative benefits. There are still some other changes brought about by 3.0-T, such as higher sensitivity to motion, susceptibility effect, more difference in resonant frequency among different metabohies, and so on. These features may be a double-edged sword in structural and functional imaging. But with the ceaseless progress of the technology and gains in experience, 3.0-T systems will provide more information and show more advantages.

MRI Brain Tumor Segmentation with Intuitionist Possibilistic Fuzzy Clustering and Morphological Operations

Digital Image Processing(DIP)is a well-developed field in the biological sciences which involves classification and detection of tumour.In medical science,automatic brain tumor diagnosis is an important phase.Brain tumor detection is performed by Computer-Aided Diagnosis(CAD)systems.The human image creation is greatly achieved by an approach namely medical imaging which is exploited for medical and research purposes.Recently Automatic brain tumor detection from MRI images has become the emerging research area of medical research.Brain tumor diagnosis mainly performed for obtaining exact location,orientation and area of abnormal tissues.Cancer and edema regions inference from brain magnetic resonance imaging(MRI)information is considered to be great challenge due to brain tumors complex structure,blurred borders,besides exterior features like noise.The noise compassion is mainly reduced along with segmentation stability by suggesting efficient hybrid clustering method merged with morphological process for brain cancer segmentation.Combined form of Median Modified Wiener filter(CMMWF)is chiefly deployed for denoising,and morphological operations which in turn eliminate nonbrain tissue,efficiently dropping technique’s sensitivity to noise.The proposed system contains the main phases such as preprocessing,brain tumor extraction and post processing.Image segmentation is greatly achieved by presenting Intuitionist Possibilistic Fuzzy Clustering(IPFC)algorithm.The algorithm’s stability is greatly enhanced by this clustering along with clustering parameters sensitivity reduction.Then,the post processing of images are done through morphological operations along with Hybrid Median filtering(HMF)for attaining exact tumors representations.Additionally,suggested algorithm is substantiated by comparing with other existing segmentation algorithms.The outcomes reveal that suggested algorithm achieves improved outcomes pertaining to accuracy,sensitivity,specificity,and recall.

Measurement, modelling, and closed-loop control of crystal shape distribution： Literature review and future perspectives

Crystal morphology is known to be of great importance to the end-use properties of crystal products, and to affect down-stream processing such as filtration and drying. However, it has been previously regarded as too challenging to achieve automatic closed-loop control. Previous work has focused on controlling the crystal size distribution, where the size of a crystal is often defined as the diameter of a sphere that has the same volume as the crystal. This paper reviews the new advances in morphological population balance models for modelling and simulating the crystal shape distribution （CShD）, measuring and estimating crystal facet growth kinetics, and two- and three-dimensional imaging for on-line characterisation of the crystal morphology and CShD. A framework is presented that integrates the various components to achieve the ultimate objective of model-based closed-loop control of the CShD. The knowledge gaps and challenges that require further research are also identified.